What about the Fisher scoring algorithm? Fisher’s scoring algorithm is a derivative of Newton’s method for solving maximum likelihood problems numerically.
For model1 we see that Fisher’s Scoring Algorithm needed six iterations to perform the fit.
This doesn’t really tell you a lot that you need to know, other than the fact that the model did indeed converge, and had no trouble doing it.